Substantial fluctuations in pain intensity across time and/or individuals have been shown in many studies. Variability in pain intensity is not simply a byproduct of different measurement approaches and is influenced by a multitude of factors. For example, demographic (e.g. younger age or higher body mass index), cognitive and psychological factors (e.g. using distraction strategies as opposed to focusing on pain, higher levels of depressive symptoms) and neurophysiological factors (e.g. greater amplitude in gamma oscillations) have been associated with higher pain intensity variability.
Goal
People recall a past experience mostly based on how they felt at the peak of the situation, and how they felt most recently. This is the peak-and-end effect which influences one’s memory of a situation or experience. Because of this effect, measuring pain as a dynamic process in real-time using methodologies such as ecological momentary assessment (EMA) offers significant advantages. The research team report on an EMA study designed to (1) describe the extent and stability of variability in pain intensity among participants living with chronic low back pain; (2) identify demographic and psychosocial predictors of variability in pain intensity; and (3) examine the associations between variability in pain intensity and psychosocial outcomes (like quality of life and disability) and health care utilization (e.g. number of health care providers consulted, polypharmacy).
Methodology
The study included 140 adult participants living with chronic low back pain (more than three months duration) for which they have consulted a health care provider about their pain in the last two months. Individuals completed baseline questionnaires, which tapped into pain characteristics, psychosocial characteristics and demographic information. Participants were instructed to complete a momentary pain intensity diary using an interval-based prompting design at each of the following times: 1) when they got up in the morning; 2) twice randomly during the day when they heard the auditory signal programmed to beep between 9:00 AM and 12:00 PM and again between 1:00 PM and 6:00 PM); 3) just before taking pro re nata (P.R.N.) pain killers; and 4) before going to bed in the evening. Using a linear hierarchical location scale model with a normal likelihood function, the researchers aimed to quantify the intra-individual variability in momentary pain intensity ratings across the two 7-day recording periods.
Main findings
Results showed great variability within individuals in pain ratings over the two weeks. However, this variability was not associated with physical and mental health-related quality of life, pain interference, number of health care providers consulted, and polypharmacy. The study did not identify predictors of this intra-individual pain intensity variability. In contrast, other measures of pain derived from EMAs in other studies, such as maximum pain, pain intensity variability or amount of time in high pain, were associated with some aspects of physical functioning, depressive symptoms, and social functioning.
Take home message
Pain intensity variability differs across patients yet correlates remain difficult to understand. These findings show that pain intensity variability on its own might not capture the full impact of fluctuating pain levels on patient‘s functioning, psychosocial outcomes and health care utilization.
